Robust head segmentation method based on level set model in complex scenes
复杂背景下基于level set模型的头部分割算法

In office setting,head segmentation becomes difficult in the scene with occlusion or frequent brightness change.To deal with such problems,a robust head segmentation method based on level set model was proposed.After head level set model was constructed by sign distance function,the difference between head level set model and sign distance function of an image was added to Chan-Vese segmentation formula.Then a new Euler-Lagrange formula was obtained.When the evolvement of the sign distance function in the new Euler-Lagrange formula stopped,the head segmentation was finished.The experiments were implemented separately in office setting with scenes of two-person occlusion,Gaussian noise,and brightness change.Compared with Chan-Vese segmentation,the provided head segmentation method is robust to above three complex scenes.